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| Two-phase Flow Pattern Recognition Based on Electrical Capacitance Tomography Reconstructed Images |
| WANG Xiao-xin1,WANG Bo2,CHEN Yang-zheng1,HU Hong-li3 |
1. Shaanxi Key Laboratory of Photoelectric Sensing Logging,Xi’an Shiyou University, Xi’an, Shaanxi 710065, China
2. Geophysical Exploration Technology and Equipment R&D Center, Xi’an Research Institute of China Coal Technology ＆ Engineering Group Corp, Xi’an, Shaanxi 710077, China
3. State Key Laboratory of Electrical Insulation & Power Equipment, Xi’an Jiaotong University, Xian, Shaanxi 710049, China |
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Abstract To realize the industrial multiphase flow pattern recognition, based on the research of process tomography, the reconstructed image information is analyzed and processed simply and efficiently, the two-dimensional maximum entropy threshold segmentation technique and the genetic algorithm optimized neural network classifier are used to realize the flow pattern identification.Three typical gas-solid flow patterns were verified on the two-phase flow pneumatic transport platform by the mentioned method.The experimental results showed that the recognition accuracy is 94.7%.
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Received: 22 November 2018
Published: 13 August 2020
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2020, Vol. 41 
